The Mills Lab review modern approaches for investigating structural variations (SV) and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.
Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression of tens of thousands of single cells simultaneously. We present DeepImpute, a deep neural network-based imputation algorithm that uses dropout layers and loss functions to learn patterns in the data, allowing for accurate imputation.
“When you first begin looking at new data like this, it’s like landing on Mars and looking around for the first time, but a Mars with little critters never described before staring back at you,” said Melissa Duhaime, assistant professor of ecology and evolutionary biology & CCMB affiliated faculty member, commenting on the discovery of
Three CCMB faculty members will be funded this fiscal year through the presidential initiative , which aims to create globally leading bio-sciences research programs focused on solving critical problems.
Bioinformatics students Wei Zhou, Brooke Wolford, Ellen Schmidt and Ryan Crawford, DCMB and CCMB faculty Michael Boehnke, Goncalo Abecasis, Hyun Kang also were part of the team, as were many other UM and Norwegian scientists.